Multi-Sensor Data Collection, Fusion, and Analytics to Support Effective Performance Measures in Construction Projects

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Although there is still a debate on whether construction productivity is declining or not, one note of agreement is that the room for improvement is significant. Consider an often-repeated phrase that “You can't improve what you don't measure.” Therefore, providing the effective measures of construction productivity becomes essential and has been identified as one of five opportunities for breakthrough improvements in construction efficiency and competitiveness in the next 2 to 10 years. The objective of this research is to investigate the feasibility of integrating multi-sensory data from video, acoustic, thermal, and other Internet of Things (IoT) sensors to facilitate the measures of construction operation productivity on a construction site. The proposed research work includes three main steps. It starts with the design of a portable multi-sensor hardware platform that could be easily deployed to monitor onsite construction operations. Then, the data fusion and analysis are conducted to retrieve construction operation information from the monitoring data. The retrieved information is further explored to discover and model real construction operation processes on the site. This way, the productivity of the construction operations in the processes could be measured and analyzed in a systematic way with less time, cost, and efforts required. The research is expected to help contractors and/or subcontractors evaluate the efficiency of their work more often (e.g. on an hourly or daily basis), so that the productivity problems on active construction projects could be detected and corrected quickly. The effectiveness of the research work will be evaluated in real construction projects in Quebec, Canada.